Fontanelle, IA
Fontanelle, IA's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Fontanelle lands at the 48th percentile for wildfire risk to structures — modestly above the national average for wildfire risk — a figure built from its 519 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Fontanelle at the 48th percentile, close to its 48th-percentile risk score.
What "at risk" means for the buildings here
Fontanelle rates 81.3% Minimal exposure against just 18.7% Direct and 0% Indirect — of 519 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.
Fontanelle against the rest of the country
Within Iowa, Fontanelle ranks higher (66th percentile) than it does nationally (48th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Fontanelle ranks 16,474 for wildfire risk (1 is highest) and 17,039 by building count (1 is largest). Within Iowa alone, it ranks 347 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.
Shopping for coverage in Fontanelle
Fontanelle's elevated rating (48th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Lowering exposure, not just insuring around it
Even with 81.3% of Fontanelle outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Fontanelle's figures come from
Fontanelle's 48th-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Fontanelle's dominant minimal exposure actually means, with real examples from across the dataset.